Promoting Workforce Development using CAVe-In-A-Box and Computer Vision based VRU Detection

As CAV technologies move from research to deployment phase, the FHWA and USDOT Intelligent Transportation Systems Joint Program Office (ITSJPO) Professional Capacity Building (PCB) program have identified the need to educate the workforce that will be needed to deploy, operate, and maintain these technologies. Based on this need, the Connected and Automated Vehicle Education (CAVe) series of educational tools were developed. This series of tools focus on teaching users the data flows that exist in an ITS environment and how each equipment generates, handles, or processes CAV data. With the desire to educate a wide audience, the educational material that accompanies the hardware can be used to help users learn how to operate the equipment or be used as supplementary material to a greater topic, such as computer networking or wireless communications.

This paper presents lessons learned through intensive workforce development projects with the USDOT ITSJPO PCB initiative CAVe. With the support of Ohio Department of Transportation (ODOT) and DriveOhio Student Transportation Advancement Research (STAR) award, the University of Cincinnati Infrastructure Institute (UCII) team has assembled CAVe-In-A-Box and CAVe-Lite Infrastructure and Mobile kits. In this project, the CAVe-In-A-Box has been utilized as a demonstration tool to present the real-world benefits such as vulnerable road users’ (VRU) safety at intersections and the CAVe-Lite is used to engage 5-12 grade students in a scaled desktop smart mobility technology deployment. To simplify the CAVe demonstrations and engagement for young learners, CAVe-Lite Infrastructure and Mobile kits have been assembled with a small LED based signal head, Raspberry Pi as controllers and a scaled RC monster truck for mobile kit. Two main workforce development projects are highlighted in this paper: 1) demonstration with CAVe-In-A-Box at Aiken New Tech high school (8^th grade students), Cincinnati Public Schools and 2) engagement with CAVe-Lite at UC College of Engineering and Applied Sciences (CEAS) student camps (5-12 grade students from different states in the US and Japan).

The scope of this paper is to: 1) briefly explain the process to assemble CAVe-In-A-Box and CAVe-Lite Infrastructure and Mobile kits; 2) lesson plans and case-based learning approaches to engage young learners (i.e., 5-12 grade students) in CAVe; and 3) discuss pre- and post-assessment results from the engagement sessions to test the approach.

With an experiential learning of CAVs through real-time pedestrian detection with computer vision and AI, high school students participated in the summer camp have demonstrated enhanced knowledge in smart mobility. Specifically, as post assessment results indicated, about 20% more students expressed their interest in pursuing a career in transportation. Majority of students indicated increased level of knowledge in smart mobility due to their experiential learning with Raspberry Pi, python programming, CAVs, AVs, EVs, and V2X technologies. From the results, it is important to note that definitions of words used in smart mobility such as ‘connected’, ‘automated’, and ‘autonomous’ need more example-based learning methods for students to understand their real-world applications.

 


Note: These preliminary results are shared for publication during an active research project sponsored by ODOT Office of Research.